Dataset Information

EQTL of bronchial epithelial cells and bronchial alveolar lavage deciphers GWAS-identified asthma genes.

ABSTRACT: BACKGROUND:Genome-wide association studies (GWASs) have identified various genes associated with asthma, yet, causal genes or single nucleotide polymorphisms (SNPs) remain elusive. We sought to dissect functional genes/SNPs for asthma by combining expression quantitative trait loci (eQTLs) and GWASs. METHODS:Cis-eQTL analyses of 34 asthma genes were performed in cells from human bronchial epithelial biopsy (BEC, n = 107) and from bronchial alveolar lavage (BAL, n = 94). RESULTS:For TSLP-WDR36 region, rs3806932 (G allele protective against eosinophilic esophagitis) and rs2416257 (A allele associated with lower eosinophil counts and protective against asthma) were correlated with decreased expression of TSLP in BAL (P = 7.9 × 10(-11) and 5.4 × 10(-4) , respectively) and BEC, but not WDR36. Surprisingly, rs1837253 (consistently associated with asthma) showed no correlation with TSLP expression levels. For ORMDL3-GSDMB region, rs8067378 (G allele protective against asthma) was correlated with decreased expression of GSDMB in BEC and BAL (P = 1.3 × 10(-4) and 0.04) but not ORMDL3. rs992969 in the promoter region of IL33 (A allele associated with higher eosinophil counts and risk for asthma) was correlated with increased expression of IL33 in BEC (P = 1.3 × 10(-6) ) but not in BAL. CONCLUSIONS:Our study illustrates cell-type-specific regulation of the expression of asthma-related genes documenting SNPs in TSLP, GSDMB, IL33, HLA-DQB1, C11orf30, DEXI, CDHR3, and ZBTB10 affect asthma risk through cis-regulation of its gene expression. Whenever possible, disease-relevant tissues should be used for transcription analysis. SNPs in TSLP may affect asthma risk through up-regulating TSLP mRNA expression or protein secretion. Further functional studies are warranted.

SUBMITTER: Li X

PROVIDER: S-EPMC4583797 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

eQTL of bronchial epithelial cells and bronchial alveolar lavage deciphers GWAS-identified asthma genes.

Li X X Hastie A T AT Hawkins G A GA Moore W C WC Ampleford E J EJ Milosevic J J Li H H Busse W W WW Erzurum S C SC Kaminski N N Wenzel S E SE Meyers D A DA Bleecker E R ER

Allergy 20150724 10

<h4>Background</h4>Genome-wide association studies (GWASs) have identified various genes associated with asthma, yet, causal genes or single nucleotide polymorphisms (SNPs) remain elusive. We sought to dissect functional genes/SNPs for asthma by combining expression quantitative trait loci (eQTLs) and GWASs.<h4>Methods</h4>Cis-eQTL analyses of 34 asthma genes were performed in cells from human bronchial epithelial biopsy (BEC, n = 107) and from bronchial alveolar lavage (BAL, n = 94).<h4>Results ...[more]

PMID: 26119467

Similar Datasets

Project description:PURPOSE:Osteoporosis is a common global health problem characterized by low bone mineral density (BMD) and increased risk of fracture. Genome-wide association studies (GWAS) have identified >100 genetic loci associated with BMD. However, the functional genes responsible for most associations remain largely unknown. We conducted an innovative summary statistic data-based Mendelian randomization (SMR) analysis to identify novel causal genes associated with BMD and explored their potential functional significance. METHODS:After quality control of the largest GWAS meta-analysis data of BMD and the largest expression quantitative trait loci (eQTL) meta-analysis data from peripheral blood samples, 5967 genes were tested using the SMR method. Another eQTL data was used to verify the results. Next we performed a fine-mapping association analysis to investigate the functional SNP in the identified loci. Weighted gene co-expression network analysis (WGCNA) was used to explore functional relationships for the identified novel genes with known putative osteoporosis genes. Further, we assessed functions of the identified genes through in vitro cellular study or previous functional studies. RESULTS:We identified two potentially causal genes (ASB16-AS1 and SYN2) associated with BMD. SYN2 was a novel osteoporosis candidate gene and ASB16-AS1 locus was known to be associated with BMD but was not the nearest gene to the top GWAS SNP. Fine-mapping association analysis showed that rs184478 and rs795000 was predicted to be possible causal SNPs in ASB16-AS1 and SYN2, respectively. ASB16-AS1 co-expressed with several known putative osteoporosis risk genes. In vitro cellular study showed that over-expressed ASB16-AS1 increased the expression of osteoblastogenesis related genes (BMP2 and ALPL), indicating its functional significance. CONCLUSION:Our findings support that ASB16-AS1 and SYN2 may represent two novel functional genes underlying BMD variation. The findings provide a basis for further functional mechanistic studies.

Project description:BackgroundSevere asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown.MethodsIn the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma.ResultsIn the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10- 6), type I diabetes mellitus (Corrected P = 7.09 × 10- 5), and asthma (Corrected P = 1.72 × 10- 3). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (PeQTL = 2.98 × 10- 8 and PGWAS = 3.40 × 10- 8), rs11265180 (PeQTL = 6.0 × 10- 6 and PGWAS = 1.99 × 10- 3), and rs1867087 (PeQTL = 1.0 × 10- 4 and PGWAS = 1.84 × 10- 5) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10- 6).ConclusionsOur current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.

Dataset Information

EQTL of bronchial epithelial cells and bronchial alveolar lavage deciphers GWAS-identified asthma genes.

Publications

eQTL of bronchial epithelial cells and bronchial alveolar lavage deciphers GWAS-identified asthma genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets